Anesthetics, sedatives and paralytic agents are frequently used by physicians to control the levels of hypnosis, analgesia and muscle relaxation in patients undergoing surgical or medical procedures, recovering from surgery, or receiving medical treatment. Monitoring the effects of these agents on the patient is useful for ensuring efficacious drug administration to achieve the desired effect as well as to detect (or predict) untoward events. For example, the use of EEG monitoring to measure the effects of anesthetics on the brain is useful to help titrate agents to a desired level of anesthesia and to prevent intraoperative awareness (from underdosing) or hemodynamic depression (from overdosing). In addition, the use of intraoperative EEG monitoring (as quantified, for example, by the Bispectral Index.TM. which is an index produced by monitoring equipment sold by Aspect Medical Systems, Inc. the assignee of the present application) has been shown to improve the utilization of anesthetics and to improve the speed and quality of patient recovery. Improvements in methods that measure and analyze the effects of anesthetics (as reflected in changes in measured biopotentials) will provide opportunities for enhanced patient care and resource utilization.
The acquisition of high fidelity biopotentials such as the electroencephalogram (EEG), the electromyogram (EMG) or the electrooculogram (EOG) is frequently essential for many diagnostic tests or for patient monitoring. The accuracy of automated analysis of biopotentials is strongly coupled with the signal quality of the acquired data. In addition, the development of algorithms which extract information from biopotentials is bounded by the range of signal features that are uncorrupted by noise. By acquiring higher fidelity signals, additional and more subtle features of the signal are available for analysis.
EEG, EMG and EOG provide useful and complementary information regarding the effect of anesthetics (and other factors) on a patient. The spontaneous EEG as measured using surface electrodes reflects the cortical activity of the brain localized near the electrodes. Cortical activity can be modulated by changes in cortical cellular function (caused by changes in metabolic needs, hypoxia, cooling or drugs) or by changes in function of subcortical structures that communicate with the cortex (e.g., the reticular activation system which organizes sleep activity). In general, as the depth of anesthesia increases to induce unconsciousness, the EEG power increases while the EEG bandwidth decreases. Consequently, the EEG provides a direct measure of the effects of anesthetics on the brain. For example, it has been demonstrated that the EEG (as quantified by the Bispectral Index) correlates with level of sedation and memory in volunteers.
Similarly, basal muscle tone is modulated by the brain and by factors local to a muscle. Unconsciousness induces a state of relaxation which is reflected in decreased nervous stimulation of muscle and thus decreased EMG power. (The muscle's response to transdermal electrical stimulation is frequently used to assess the degree of pharmacological paralysis and can be used to determine if low EMG power is a result of unconsciousness or paralysis.) In contrast, patient movement or grimacing during surgery generates bursts of EMG on the scalp (i.e., sudden increases in EMG power) which may be used by a monitor to detect a state of insufficient anesthesia.
Eye motion and eye blinks generate potentials that are measured by periorbital electrodes. Detection of eye blinks is useful to confirm consciousness while detection of rapid eye motion is generally indicative of sleep. Slow eye rolling is frequently associated with drowsiness. Thus, the EEG, EMG and EOG provide useful information regarding the state of the patient during anesthesia.
Although EEG, EMG and EOG are the resultant signals generated from different sources beneath the skin, these biopotentials mingle on the scalp where surface electrodes are used to collect the signals. Moreover, scalp electrodes are susceptible to artifacts generated by electrode motion.
Although most of the spectral power of the EEG is in frequencies lower than the high frequency EMG, the spectra of the two signals overlap. Nevertheless, one common approach to improving the perceived signal quality of the EEG is to low pass filter the acquired signals to diminish the high frequency EMG in the EEG (and to high pass filter the signals to diminish the effects of the EEG in the EMG). This is a modestly effective approach in improving the signal quality; however, the cost of this approach is the loss of information that exists in the overlapping band between spectra of the EEG and the EMG.
U.S. Pat. Nos. 4,112,930 and 4,170,227 issued to Feldman describe an electrode configuration of two pairs of neighboring electrodes (i.e., 2 well-separated sets of 2 closely spaced electrodes (plus a fifth electrode as a common ground)) for the purpose of collecting ECG and artifact signals in order to detect the presence of electrode motion artifact to prevent false arrhythmia alarms. In U.S. Pat. No. 4,112,930, the configuration is used to extract 1 ECG signal (measured between one electrode from each pair) and 2 artifact signals (each measured between electrodes within a pair). Alternatively, in U.S. Pat. No. 4,170,227, the same configuration is used to measure 2 ECG signals (1 being the same as above, and the second being between the remaining 2 electrodes). In this case, an artifact signal is derived from the 2 ECG signals by taking their difference.
In both patents issued to Feldman, the presence of artifact is detected in the artifact signal to inhibit processing of the ECG signal (and to disable arrhythmia alarms). The artifact is NOT used to reduce artifact in the ECG signal, but Feldman suggests that one could use the artifact signal to "restore" the ECG signal. Feldman expressly describes a method and apparatus of collecting the signals to detect baseline wander.
Feldman, in an article entitled "A new electrode system for automated ECG monitoring", (Computers in Cardiology, 1979, pp285-288) reported on the performance of his baseline artifact detection system in rejecting false arrhythmia alarms. Here he also introduces the "Smart bi-lectrode", a concentric pair of electrodes (i.e., a center disc surrounded by an annulus). The use of a concentric pair of electrodes was also described in U.S. Pat. No. 3,868,947 issued to Hoslinger. Hoslinger, however, used the 2 pairs of concentric electrodes for artifact compensation (not artifact detection like Feldman). Hoslinger connects together and grounds the outer annulus of each concentric pair. Hoslinger only describes the configuration of the concentric electrodes, with the outer electrodes being connected together and to ground.
In International Application No. PCT/US95/14889 filed by Albrecht, an apparatus and method is described for using related signals from multiple electrodes to reduce noise in ECGs. This PCT application describes a method of injecting high frequency current in order to extract electrode impedance and respiration information while the ECG and baseline wander is simultaneously collected. To do this, multi-segmented electrodes are used in which 3 outer annular segments closely surround a central disc.
The method taught by Albrecht assumes a deterministic, repeating signal (like an ECG) i.e., the data is processed by aligning epochs (of individual beats) relative to a repeating characteristic of the signal (e.g., the R wave), calculating the correlation among all channels for a given beat, averaging the correlation over the recent set of beats, and using this correlation noise measure to select the combination of input channels that will produce a noise-reduced version as an output. This process is obviously not applicable to processing a random, non-repeating signal (like the EEG).
Other prior art describes methods of adaptively removing one signal from another by estimating a transfer function between primary and secondary signals, predicting the "noise" component in the primary signal using the transfer function applied to the secondary signal, and subtracting the predicted noise from the measured signal.
It is therefore a principal object of the present invention to provide a means to collect and uncouple the EEG, EMG and EOG in order to enhance the fidelity of these desired signals.
Another object of the present invention is to provide an electrode designed to enhance the uncoupling of the EEG, EMG and EOG signals.
Still another object of the present invention is to provide a system and method to reduce artifacts due to electrode motion.